In order to validate our proposal (schematically depicted in Fig. REF ), we make use of a vanilla UNet model [1]} and incorporate an additional loss term in the form of the proposed SLICLoss. In our experiments, we compared our method with a baseline model using only the BCE loss on different modalities for BE in EndoUDA. The rationale for this case study is to assess if the proposed loss is capable of improving the network's generalisation capabilities for segmenting images containing a significant domain shift.
